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#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/registration/icp.h>
int
main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_in (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZ>);
// Fill in the CloudIn data
cloud_in->width = 5;
cloud_in->height = 1;
cloud_in->is_dense = false;
cloud_in->points.resize (cloud_in->width * cloud_in->height);
for (size_t i = 0; i < cloud_in->points.size (); ++i)
{
cloud_in->points[i].x = 1024 * rand () / (RAND_MAX + 1.0f);
cloud_in->points[i].y = 1024 * rand () / (RAND_MAX + 1.0f);
cloud_in->points[i].z = 1024 * rand () / (RAND_MAX + 1.0f);
}
std::cout << "Saved " << cloud_in->points.size () << " data points to input:"
<< std::endl;
for (size_t i = 0; i < cloud_in->points.size (); ++i) std::cout << " " <<
cloud_in->points[i].x << " " << cloud_in->points[i].y << " " <<
cloud_in->points[i].z << std::endl;
*cloud_out = *cloud_in;
std::cout << "size:" << cloud_out->points.size() << std::endl;
for (size_t i = 0; i < cloud_in->points.size (); ++i)
cloud_out->points[i].x = cloud_in->points[i].x + 0.7f;
std::cout << "Transformed " << cloud_in->points.size () << " data points:"
<< std::endl;
for (size_t i = 0; i < cloud_out->points.size (); ++i)
std::cout << " " << cloud_out->points[i].x << " " <<
cloud_out->points[i].y << " " << cloud_out->points[i].z << std::endl;
pcl::IterativeClosestPoint<pcl::PointXYZ, pcl::PointXYZ> icp;
icp.setInputSource(cloud_in);
icp.setInputTarget(cloud_out);
pcl::PointCloud<pcl::PointXYZ> Final;
icp.align(Final);
std::cout << "has converged:" << icp.hasConverged() << " score: " <<
icp.getFitnessScore() << std::endl;
std::cout << icp.getFinalTransformation() << std::endl;
return (0);
}
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